Coverage and power in genomewide association studies

Am J Hum Genet. 2006 May;78(5):884-888. doi: 10.1086/503751. Epub 2006 Mar 17.


The ability of genomewide association studies to decipher genetic traits is driven in part by how well the measured single-nucleotide polymorphisms "cover" the unmeasured causal variants. Estimates of coverage based on standard linkage-disequilibrium measures, such as the average maximum squared correlation coefficient (r2), can lead to inaccurate and inflated estimates of the power of genomewide association studies. In contrast, use of the "cumulative r2 adjusted power" measure presented here gives more-accurate estimates of power for genomewide association studies.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Chromosome Mapping
  • Genetic Variation
  • Genome, Human*
  • Humans
  • Linkage Disequilibrium*
  • Models, Statistical
  • Polymorphism, Single Nucleotide
  • Quantitative Trait, Heritable*